Fan Hong created FLINK-32889:
--------------------------------
Summary: BinaryClassificationEvaluator gives wrong weighted AUC
value
Key: FLINK-32889
URL: https://issues.apache.org/jira/browse/FLINK-32889
Project: Flink
Issue Type: Bug
Components: Library / Machine Learning
Affects Versions: ml-2.3.0
Reporter: Fan Hong
BinaryClassificationEvaluator gives wrong AUC value when a weight column
provided.
Here is an case from the unit test. The (score, label, weight) of data are:
{code:java}
(0.9, 1.0, 0.8),
(0.9, 1.0, 0.7),
(0.9, 1.0, 0.5),
(0.75, 0.0, 1.2),
(0.6, 0.0, 1.3),
(0.9, 1.0, 1.5),
(0.9, 1.0, 1.4),
(0.4, 0.0, 0.3),
(0.3, 0.0, 0.5),
(0.9, 1.0, 1.9),
(0.2, 0.0, 1.2),
(0.1, 1.0, 1.0)
{code}
PySpark and scikit-learn gives a AUC score of 0.87179, while Flink ML
implementation gives 0.891168.
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
